A UML-based approach for modeling industrial control applications

The main purpose of the poster is to present how the Unified Modeling Language (UML) can be used for diagnosing and optimizing real industrial production systems. By using a car radios production line as a case study, the poster shows the modeling process that can be followed during the analysis phase of complex control applications. In order to guarantee the continuity mapping of the models, the authors propose some guidelines to transform the use cases diagrams into a single object diagram, which is the main diagram for the next phases of the development.

Tendon regeneration through a scaffold-free approach: development of tenogenic magnetic hASCs sheets

Tendon's regeneration is limited, demanding for cell-based strategies to fully restore their functionality upon injury. The concept of magnetic force-based TE(1), generally using magnetic nanoparticles may enable, for example, stem cell stimulation and/or remote control over TE constructs. Thus, we originally propose the development of magnetic cell sheets (magCSs) with tenogenic capability, aimed at promoting tendon's regeneration. A Tenomodulin (TNMD+) subpopulation was sorted from human adipose stem cells (hASCs), using TNMD-coated immunomagnetic beads(2) and used as cell source for the development of magCSs. Briefly, cells were labeled with iron oxide composite particles (Micromod) and cultured for 7 days in α-MEM medium with or without magnetic stimulation provided by a magnetic device (nanoTherics). CSs were retrieved from the plates using magnet attraction as contiguous sheets of cells within its own deposited ECM.

The potential field method and the nonlinear attractor dynamics approach: what are the differences?

One of the most popular approaches to path planning and control is the potential field method. This method is particularly attractive because it is suitable for on-line feedback control. In this approach the gradient of a potential field is used to generate the robot's trajectory. Thus, the path is generated by the transient solutions of a dynamical system. On the other hand, in the nonlinear attractor dynamic approach the path is generated by a sequence of attractor solutions. This way the transient solutions of the potential field method are replaced by a sequence of attractor solutions (i.e., asymptotically stable states) of a dynamical system. We discuss at a theoretical level some of the main differences of these two approaches.

Towards effective control of P2P traffic aggregates in network infrastructures

Nowadays, many P2P applications proliferate in the Internet. The attractiveness of many of these systems relies on the collaborative approach used to exchange large resources without the dependence and associated constraints of centralized approaches where a single server is responsible to handle all the requests from the clients. As consequence, some P2P systems are also interesting and cost-effective approaches to be adopted by content-providers and other Internet players. However, there are several coexistence problems between P2P applications and In- ternet Service Providers (ISPs) due to the unforeseeable behavior of P2P traffic aggregates in ISP infrastructures. In this context, this work proposes a collaborative P2P/ISP system able to underpin the development of novel Traffic Engi- neering (TE) mechanisms contributing for a better coexistence between P2P applications and ISPs. Using the devised system, two TE methods are described being able to estimate and control the impact of P2P traffic aggregates on the ISP network links. One of the TE methods allows that ISP administrators are able to foresee the expected impact that a given P2P swarm will have in the underlying network infrastructure. The other TE method enables the definition of ISP friendly P2P topologies, where specific network links are protected from P2P traffic. As result, the proposed system and associated mechanisms will contribute for improved ISP resource management tasks and to foster the deployment of innovative ISP-friendly systems.

Learning joint representations for order and timing of perceptual-motor sequences: a dynamic neural field approach

Many of our everyday tasks require the control of the serial order and the timing of component actions. Using the dynamic neural field (DNF) framework, we address the learning of representations that support the performance of precisely time action sequences. In continuation of previous modeling work and robotics implementations, we ask specifically the question how feedback about executed actions might be used by the learning system to fine tune a joint memory representation of the ordinal and the temporal structure which has been initially acquired by observation. The perceptual memory is represented by a self-stabilized, multi-bump activity pattern of neurons encoding instances of a sensory event (e.g., color, position or pitch) which guides sequence learning. The strength of the population representation of each event is a function of elapsed time since sequence onset. We propose and test in simulations a simple learning rule that detects a mismatch between the expected and realized timing of events and adapts the activation strengths in order to compensate for the movement time needed to achieve the desired effect. The simulation results show that the effector-specific memory representation can be robustly recalled. We discuss the impact of the fast, activation-based learning that the DNF framework provides for robotics applications.

Study of grapevine solute transporters involved in berry quality. A biochemical and molecular approach

Tese de Doutoramento em Biologia de Plantas

Lipids under stress - a lipidomic approach for the study of mood disorders

The emerging field of lipidomics has identified lipids as key players in disease physiology. Their physicochemical diversity allows precise control of cell structure and signaling events through modulation of membrane prop- erties and trafficking of proteins. As such, lipids are important regulators of brain function and have been implicated in neurodegenerative and mood disorders. Importantly, environmental chronic stress has been associated with anxiety and depression and its exposure in rodents has been extensively used as a model to study these diseases. With the accessibility to modern mass- spectrometry lipidomic platforms, it is now possible to snapshot the extensively interconnected lipid network. Here, we review the fundamentals of lipid biology and outline a framework for the interpretation of lipidomic studies as a new approach to study brain pathophysiology. Thus, lipid profiling provides an exciting avenue for the identification of disease signatures with important implications for diagnosis and treatment of mood disorders.

An evolutionary approach to the use of Petri net based models: from parallel controllers to HW/SW co-design

"A workshop within the 19th International Conference on Applications and Theory of Petri Nets - ICATPN’1998"

Object-oriented inheritance of statecharts for control applications

This paper discusses how object-oriented iuheritance can be re-interpreted if statecharts are used for modelling the dynamic behaviour of an object. The support of inheritance of statecharts allows the improvement of systems' development by easing the reutilization of parts of already developed euccessful systems, aad by promoting the iterative and continuous models' refinement advocated by the operatioaal approach. Statechart is the formalism used within UML to specify reactive state.based behaviours. This paper covers the use of statecharts within the modelling of embedded systems for industrial control applxications, where performance and memory usage are main concerns.

Antibacterial properties of multifunctional coatings Ag-ZrCN for biomedical devices: a novel approach

PhD in Sciences Specialty in Physics